摘要
作为计算机视觉领域的一个重要课题,在线目标跟踪在导弹制导、视频监控、无人机跟踪等众多领域中具有重要作用.尽管现在已有大量研究,但是仍然存在很多问题亟待解决,如光照变化、尺度变化、形变、遮挡和相机移动等.为了更清楚地梳理现存的算法,文中对典型的目标跟踪算法进行分析总结.首先,简单介绍研究意义及相关工作.然后,从传统算法和深度学习算法两方面对经典算法进行概述和分析.最后,讨论算法目前存在的问题,给出未来的研究趋势.
Online object tracking is a fundamental problem in computer vision and it is crucial to application in numerous fileds such as guided missile, video surveillance and unmanned aerial vehicle. Despite many studies on visual tracking, there are still many challenges during the tracking process including illumination variation, rotation, scale change, deformation, occlusion and camera motion. To make a c/ear understanding of visual tracking, visual tracking algorithms are summarized in this paper. Firstly, the meaning and the related work are briefly introduced. Secondly, the typical algorithms are classified, summarized and analyzed from two aspects: traditional algorithms and deep learning algorithms. Finally, the problems and the prediction of the future of visual tracking are discussed.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2018年第1期61-76,共16页
Pattern Recognition and Artificial Intelligence
关键词
目标跟踪
相关滤波
深度学习
Object Tracking, Correlation Filter, Deep Learning